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Risk-Aware Mitigation for MANET Routing Attacks.

Platform : Secure Computing

IEEE Projects Years : 2012

Risk-Aware Mitigation for MANET Routing Attacks.

Abstract
Mobile Ad hoc Networks (MANET) have been highly vulnerable to
attacks due to the dynamic nature of its network infrastructure. Among these
attacks, routing attacks have received considerable attention since it could
cause the most devastating damage to MANET. Even though there exist
several intrusion response techniques to mitigate such critical attacks,
existing solutions typically attempt to isolate malicious nodes based on
binary or naı¨ve fuzzy response decisions.
However, binary responses may result in the unexpected network
partition, causing additional damages to the network infrastructure, and
naı¨ve fuzzy responses could lead to uncertainty in countering routing
attacks in MANET. In this paper, we propose a risk-aware response
mechanism to systematically cope with the identified routing attacks. Our
risk-aware approach is based on an extended Dempster-Shafer mathematical
theory of evidence introducing a notion of importance factors. In addition,
our experiments demonstrate the effectiveness of our approach with the
consideration of several performance metrics.
System Requirements:
Hardware Requirements:
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• Ram : 512 Mb.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, VOL. 9, NO. 2, MARCH/APRIL 2012
Software Requirements:
• Operating system :- Windows XP Professional
• JDK :-1.5/ 1.6 and above
• Front End :- JAVA, Swing(JFC),
Existing System:
Several work addressed the intrusion response actions in MANET by
isolating uncooperative nodes based on the node reputation derived from
their behaviors. Such a simple response against malicious nodes often
neglects possible negative side effects involved with the response actions.
In MANET scenario, improper countermeasures may cause the unexpected
network partition, bringing additional damages to the network
infrastructure. To address the above-mentioned critical issues, more
flexible and adaptive response should be investigated. The notion of risk
can be adopted to support more adaptive responses to routing attacks in
MANET. Subjective knowledge could be retrieved from previous experience
and objective evidence could be obtained from observation while logical
reasoning requires a formal foundation. Wang et al. proposed a naı¨ve
fuzzy cost-sensitive intrusion response solution for MANET. Their cost
model took subjective knowledge and objective evidence into account but
omitted a seamless combination of two properties with logical reasoning.
Disadvantage:
However, risk assessment is still a nontrivial, challenging problem
due to its involvements of subjective knowledge, objective evidence, and
logical reasoning.
Proposed System:
We formally propose an extended D-S evidence model with
importance factors and articulate expected properties for Dempster’s rule
of combination with importance factors (DRCIF). Our Dempster’s rule of
combination with importance factors is nonassociative and weighted,
which has not been addressed in the literature.
We propose an adaptive risk-aware response mechanism with the
extended D-S evidence model, considering damages caused by both attacks
and countermeasures. The adaptiveness of our mechanism allows us to
systematically cope with MANET routing attacks.
We evaluate our response mechanism against representative attack
scenarios and experiments. Our results clearly demonstrate the
effectiveness and scalability of our risk-aware approach.
Modules:
 Evidence collection
 Risk assessment
 Decision making
 Intrusion response
 Routing table recovery
1) Evidence collection
In this step, Intrusion Detection System (IDS) gives an attack alert
with a confidence value, and then Routing Table Change Detector (RTCD)
runs to figure out how many changes on routing table are caused
by the attack.
2) Risk assessment
Alert confidence from IDS and the routing table changing
information would be further considered as independent evidences for risk
calculation and combined with the extended D-S theory. Risk of
countermeasures is calculated as well during a risk assessment phase.
Based on the risk of attacks and the risk of countermeasures, the entire
risk of an attack could be figured out.
3) Decision making
The adaptive decision module provides a flexible response decisionmaking
mechanism, which takes risk estimation and risk tolerance into
account. To adjust temporary isolation level, a user can set different
thresholds to fulfill her goal.
4) Intrusion response
With the output from risk assessment and decision-making module,
the corresponding response actions, including routing table recovery and
node isolation, are carried out to mitigate attack damages in a distributed
manner.
5) Routing table recovery
Routing table recovery is an indispensable response and should serve
as the first response method after successful detection of attacks. In
proactive routing protocols like OLSR, routing table recovery does not bring
any additional overhead since it periodically goes with routing control
messages. Also, as long as the detection of attack is positive, this response
causes no negative impacts on existing routing operations.



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